ADNI-to-BIDS

[Shahzad ALi]

Dear Alice,

I hope you are doing well.

I am having error while converting T1, FDG and AV45 PET scans in  clinica from adni-to-bids:

ValueError: For subject 109_S_1343 in session ses-M000, an error occurred whilst recentering Nifti image: /Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_T1_FDG_AV45/ADNI/109_S_1343/FDG_Brain_Em_-_Iter_Brain_Mode_/2007-04-24_07_26_33.0/I78559/ADNI_109_S_1343_PET_FDG_Brain_Em_-_Iter_Brain_Mode__br_raw_20071026071616697_S41947_I78559.vThe error is: Cannot work out file type of "/Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_T1_FDG_AV45/ADNI/109_S_1343/FDG_Brain_Em_-_Iter_Brain_Mode_/2007-04-24_07_26_33.0/I78559/ADNI_109_S_1343_PET_FDG_Brain_Em_-_Iter_Brain_Mode__br_raw_20071026071616697_S41947_I78559.v"

Please guide me in resolving this error.

Thanks & Best,

Shahzad Ali | PhD Researcher

[Alice Joubert]

Hello Ali,

I will try to reproduce. Can you remind me your setup (clinica and python version), as well as the command line you are using ?

Best,

Alice

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[Shahzad ALi]

Dear Alice,
Thanks for your response. Here are the details about setup:

(clinicaEnv) shahzadali@Shahzads-MacBook-Pro ~ % conda --version

conda 24.5.0

(clinicaEnv) shahzadali@Shahzads-MacBook-Pro ~ % python --version

Python 3.10.13

(clinicaEnv) shahzadali@Shahzads-MacBook-Pro ~ % 

I am using the following command for conversion (converting T1, FDG and AV45 PET scans in  clinica from adni-to-bids:):

clinica convert adni-to-bids /Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_T1_FDG_AV45/ADNI 

/Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_ClinicalData 

/Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_T1_FDG_AV45/BIDS_Converted

ValueError: For subject 109_S_1343 in session ses-M000, an error occurred whilst recentering Nifti image: /Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_T1_FDG_AV45/ADNI/109_S_1343/FDG_Brain_Em_-_Iter_Brain_Mode_/2007-04-24_07_26_33.0/I78559/ADNI_109_S_1343_PET_FDG_Brain_Em_-_Iter_Brain_Mode__br_raw_20071026071616697_S41947_I78559.vThe error is: Cannot work out file type of "/Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_T1_FDG_AV45/ADNI/109_S_1343/FDG_Brain_Em_-_Iter_Brain_Mode_/2007-04-24_07_26_33.0/I78559/ADNI_109_S_1343_PET_FDG_Brain_Em_-_Iter_Brain_Mode__br_raw_20071026071616697_S41947_I78559.v"

Furthermore, I tried to convert individual PET-FDG files using:

clinica convert adni-to-bids /Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_All/PET_FDG /Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_ClinicalData /Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_All/BIDS_Converted/PET_FDG_Converted -m PET_FDG

and I encountered following error:

ValueError: For subject 053_S_7086 in session ses-M000, an error occurred whilst recentering Nifti image: /Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_All/PET_FDG/053_S_7086/ADNI_Brain_PET__Raw/2022-11-07_13_56_57.0/I1639968/ADNI_053_S_7086_PET_ADNI_Brain_PET__Raw_br_raw_20221108141318761_S1174102_I1639968.iThe error is: Cannot work out file type of "/Volumes/CrucialX6/SS_ADNI/Clinica/ADNI_All/PET_FDG/053_S_7086/ADNI_Brain_PET__Raw/2022-11-07_13_56_57.0/I1639968/ADNI_053_S_7086_PET_ADNI_Brain_PET__Raw_br_raw_20221108141318761_S1174102_I1639968.i"

Furthermore, at the end of normal other conversions like fMRI, PET_TAU, PET_AMYLOID, etc. The following warning appears, is this the normal execution?

:162: PerformanceWarning: indexing past lexsort depth may impact performance.

  dxsum_df.loc[(alternative_id, "sc"), "DIAGNOSIS"].values[0]

2024-10-31 12:46:46,079:INFO:Creating sessions files...

/Users/shahzadali/miniconda3/envs/clinicaEnv/lib/python3.10/site-packages/clinica/iotools/converters/adni_to_bids/adni_utils.py:208: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`

  df_subj_sessions["a_stat"] = df_subj_sessions.apply(

/Users/shahzadali/miniconda3/envs/clinicaEnv/lib/python3.10/site-packages/clinica/iotools/converters/adni_to_bids/adni_utils.py:216: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`

  df_subj_sessions["tau_stat"] = df_subj_sessions.apply(

I will be very thankful for your help in this matter.

Best,

Shahzad Ali | PhD Researcher

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[Shahzad ALi]

apologies, The clinica version is:

% clinica --version: clinica, version 0.9.1

% python --version:  Python 3.10.13

Best,

[Alice Joubert]

Dear Ali,

Thanks for your answer. From the beginning when downloading the images for these two subjects the image format is invalid : extensions .v and .i are not managed by clinica at all. Clinica expects either nifti or dicom images. Do you know if that kind of format represents a lot of images in your dataset ? Personally, it is not a format I am familiar with.

Also, for the additional warnings appearing for session files creation it may not be optimal but clinica still outputs what is expected.

Best,

Alice